Turning k on its head: Comments on use of an ED50 in delay discounting research

Yoon, Jin Ho; Higgins, Stephen T.

doi:10.1016/j.drugalcdep.2007.12.011

Cited by 140 publications

(86 citation statements)

References 30 publications

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“…This task directly measures the Effective Delay 50% (ED 50 ) value for a given commodity, a value that is a simple inverse of the discount rate (Yoon & Higgins, 2008). This is done by presenting a series of questions between some amount of a delayed commodity and half that amount available immediately.…”

Section: Methodsmentioning

confidence: 99%

A 5-trial adjusting delay discounting task: Accurate discount rates in less than one minute.

Koffarnus¹,

Bickel²

2014

Experimental and Clinical Psychopharmacology

326

294

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Individuals who discount delayed rewards at a high rate are more likely to engage in substance abuse, overeating, or problem gambling. Findings such as these suggest the value of methods to obtain an accurate and fast measurement of discount rate that can be easily deployed in variety of settings. In the present study, we developed and evaluated the 5-trial adjusting delay task, a novel method of obtaining discount rate in less than one minute. We hypothesized that discount rates from the 5-trial adjusting delay task would be similar and correlated with discount rates from a lengthier task we have used previously, and that four known effects relating to delay discounting would be replicable with this novel task. To test these hypotheses, the 5-trial adjusting delay task was administered to 111 college students six times to obtain discount rates for six different commodities, along with a lengthier adjusting amount discounting task. We found that discount rates were similar and correlated between the 5-trial adjusting delay task and the adjusting amount task. Each of the four known effects relating to delay discounting was replicated with the 5-trial adjusting delay task to varying degrees. First, discount rates were inversely correlated with amount. Second, discount rates between past and future outcomes were correlated. Third, discount rates were greater for consumable rewards than with money, although we did not control for amount in this comparison. Fourth, discount rates were lower when zero amounts opposing the chosen time point were explicitly described. Results indicate that the 5-trial adjusting delay task is a viable, rapid method to assess discount rate.

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Section: Methodsmentioning

confidence: 99%

A 5-trial adjusting delay discounting task: Accurate discount rates in less than one minute.

Koffarnus¹,

Bickel²

2014

Experimental and Clinical Psychopharmacology

326

294

View full text Add to dashboard Cite

show abstract

“…Parameters were log transformed prior to statistical comparisons (Yoon and Higgins, 2008). Results from the adjusting amount task and the 5-trial adjusting tasks were compared using a Pearson’s product-moment correlation coefficient.…”

Section: Methodsmentioning

confidence: 99%

“…The delay to the larger amount adjusts over five trials based on participant responses. The final delay (i.e., ED 50 ) following these adjustments provides the discounting parameter for that participant (Yoon and Higgins, 2008). Koffarnus and Bickel (2014) demonstrated that this 5-trial adjusting delay task provides similar k s compared to traditional adjusting amount tasks.…”

Section: Introductionmentioning

confidence: 99%

Effects of delay and probability combinations on discounting in humans

Cox

Dallery

2016

Behavioural Processes

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To determine discount rates, researchers typically adjust the amount of an immediate or certain option relative to a delayed or uncertain option. Because this adjusting amount method can be relatively time consuming, researchers have developed more efficient procedures. One such procedure is a 5-trial adjusting delay procedure, which measures the delay at which an amount of money loses half of its value (e.g., $1000 is valued at $500 with a 10-year delay to its receipt). Experiment 1 (n = 212) used 5-trial adjusting delay or probability tasks to measure delay discounting of losses, probabilistic gains, and probabilistic losses. Experiment 2 (n = 98) assessed combined probabilistic and delayed alternatives. In both experiments, we compared results from 5-trial adjusting delay or probability tasks to traditional adjusting amount procedures. Results suggest both procedures produced similar rates of probability and delay discounting in six out of seven comparisons. A magnitude effect consistent with previous research was observed for probabilistic gains and losses, but not for delayed losses. Results also suggest that delay and probability interact to determine the value of money. Five-trial methods may allow researchers to assess discounting more efficiently as well as study more complex choice scenarios.

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“…ED50 is computed by setting the discounted value of the larger–later reward as 0.5 (half the value of the objective amount of that reward, normalized to 1) and solving for delay D (Yoon & Higgins, 2008). In the context of the Mazur model, the natural log of k typically satisfies parametric modeling assumptions better than the untransformed k ; that is, for the Mazur model,

ED 50 = \frac{1}{k}

(Yoon & Higgins, 2008), and ln(ED50) = −ln( k ) (Washio et al, 2011). Because statistical inference is generally invariant to linear transformation, inference based on ln( k ) is identical to statistical inference based on ln(ED50) if the Mazur model is adopted.…”

Section: Methodsmentioning

confidence: 99%

Accurate characterization of delay discounting: A multiple model approach using approximate bayesian model selection and a unified discounting measure

Franck

Koffarnus

House

et al. 2014

J Exper Analysis Behavior

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The study of delay discounting, or valuation of future rewards as a function of delay, has contributed to understanding the behavioral economics of addiction. Accurate characterization of discounting can be furthered by statistical model selection given that many functions have been proposed to measure future valuation of rewards. The present study provides a convenient Bayesian model selection algorithm that selects the most probable discounting model among a set of candidate models chosen by the researcher. The approach assigns the most probable model for each individual subject. Importantly, effective delay 50 (ED50) functions as a suitable unifying measure that is computable for and comparable between a number of popular functions, including both one- and two-parameter models. The combined model selection/ED50 approach is illustrated using empirical discounting data collected from a sample of 111 undergraduate students with models proposed by Laibson (1997); Mazur (1987); Myerson & Green (1995); Rachlin (2006); and Samuelson (1937). Computer simulation suggests that the proposed Bayesian model selection approach outperforms the single model approach when data truly arise from multiple models. When a single model underlies all participant data, the simulation suggests that the proposed approach fares no worse than the single model approach.

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Turning k on its head: Comments on use of an ED50 in delay discounting research

Cited by 140 publications

References 30 publications

A 5-trial adjusting delay discounting task: Accurate discount rates in less than one minute.

A 5-trial adjusting delay discounting task: Accurate discount rates in less than one minute.

Effects of delay and probability combinations on discounting in humans

Accurate characterization of delay discounting: A multiple model approach using approximate bayesian model selection and a unified discounting measure

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